modelscope/ms-swift holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Vitality (100/100) and lowest on Security (44/100). It was last updated today. A single contributor accounts for most of its recent work.
94
overall / 100
Exceptional
Software health index
Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.
94
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
Score profile
Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.
The weighted overall 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).
Direct dependencies free of known advisories — 3 affected: pillow 11.3.0 (critical 9.1), gradio 5.50.0 (high 8.6), datasets 4.8.4 (unknown)
10/25
Indirect dependencies free of known advisories — 1 affected: starlette 0.52.1 (high 7.5)
24.5/40
No advisories left outstanding — 3 advisory-carrying package(s) unaddressed past 90 days; oldest published 197 days ago
Inputs used
source
osv
advisories
60
affected_packages
4
assessed_packages
129
unassessed_packages
0
affected_by_severity
critical 1, high 2, unknown 1
direct_affected_packages
3
Matched the pypi:ms_swift@4.5.2 runtime dependency closure — what installing the published package pulls in — 129 packages. Reachability is not analyzed.
How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.
API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20
MCP server — not applicable to this kind of software
40/40
Runnable examples — examples, notebooks, sample
Inputs used
example_dirs
examples, notebooks, sample
has_mcp_signal
no
api_schema_files
—
interfaces_expected_of
—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.
Key facts
15,386GitHub stars
100contributors
1,282commits, last 12 months
0days since last push
100releases
1bus factor
537open issues
PyPIpackage ecosystems
Data collection warnings
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
First-time contributor figures cover 12 of 28 authors (cap 12)
More detail
Star and fork history 0 ★ / 1,636 ⇿
0Stars
1,636Forks
58Releases
When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.
Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.
Major 1Minor 13Patch 44
Each point covers 2 days.
OpenSSF Scorecard 4.4 / 10
4.4aggregate
Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-08-27 21:54 UTC
Full resolved dependency set from the GitHub dependency graph: 0 direct and 62 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
Registry
Package
Version
Relation
PyPI
accelerate
—
indirect
PyPI
addict
—
indirect
PyPI
aiohttp
—
indirect
PyPI
attrdict
—
indirect
PyPI
binpacking
—
indirect
PyPI
charset-normalizer
—
indirect
PyPI
cpm-kernels
—
indirect
PyPI
dacite
—
indirect
PyPI
datasets
—
indirect
PyPI
decorator
—
indirect
PyPI
docutils
—
indirect
PyPI
einops
—
indirect
PyPI
evalscope
—
indirect
PyPI
expecttest
—
indirect
PyPI
fastapi
—
indirect
PyPI
flake8
—
indirect
PyPI
gradio
—
indirect
PyPI
importlib-metadata
—
indirect
PyPI
isort
—
indirect
PyPI
json-repair
—
indirect
PyPI
matplotlib
—
indirect
PyPI
mcore-bridge
—
indirect
PyPI
megatron-core
—
indirect
PyPI
modelscope
—
indirect
PyPI
myst-parser
—
indirect
PyPI
nltk
—
indirect
PyPI
numpy
—
indirect
PyPI
openai
—
indirect
PyPI
oss2
—
indirect
PyPI
pandas
—
indirect
PyPI
peft
—
indirect
PyPI
pillow
—
indirect
PyPI
pre-commit
—
indirect
PyPI
pytest
—
indirect
PyPI
pyyaml
—
indirect
PyPI
ray
—
indirect
PyPI
recommonmark
—
indirect
PyPI
requests
—
indirect
PyPI
rouge
—
indirect
PyPI
safetensors
—
indirect
PyPI
scipy
—
indirect
PyPI
sentencepiece
—
indirect
PyPI
simplejson
—
indirect
PyPI
sortedcontainers
—
indirect
PyPI
sphinx
—
indirect
PyPI
sphinx-book-theme
—
indirect
PyPI
sphinx-copybutton
—
indirect
PyPI
sphinx-markdown-tables
—
indirect
PyPI
sphinx-rtd-theme
—
indirect
PyPI
sphinxcontrib-mermaid
—
indirect
PyPI
swanlab
—
indirect
PyPI
tensorboard
—
indirect
PyPI
tiktoken
—
indirect
PyPI
torchaudio
2.7.1
indirect
PyPI
torchvision
0.22.1
indirect
PyPI
tqdm
—
indirect
PyPI
transformers
—
indirect
PyPI
transformers-stream-generator
—
indirect
PyPI
trl
—
indirect
PyPI
uvicorn
—
indirect
PyPI
yapf
0.30.0
indirect
PyPI
zstandard
—
indirect
Dependency advisories 4
Installing pypi:ms_swift@4.5.2 pulls in 129 packages, direct and transitive: 4 carry known advisories, of which 3 are direct dependencies.
Package
Version
Relation
Severity
Advisories
Fixed in
pillow
11.3.0
direct
critical
36
12.3.0
gradio
5.50.0
direct
high
13
6.16.0
starlette
0.52.1
indirect
high
10
1.3.1
datasets
4.8.4
direct
unknown
1
5.0.1
An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.
Raw JSON report machine-readable
Feedback
Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.
Related records
Inspected repositories sharing catalogue tags or ecosystems with modelscope/ms-swift. Read them side by side →
Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.
Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.